Author(s)

Zhai Linlin ¹, Fu Jiajie ¹

Affiliation(s)

¹ Shanghai Technical Institute of Electronics & Information, Wahong Highway, Shanghai, China

Corresponding Author

Zhai Linlin

ABSTRACT

Aiming at the problems of high search randomness, poor target bias, and low path quality in traditional robotic arm path planning algorithms, a Bidirectional Target-Biased APF-Informed-RRT* (BTB-APF-Informed-RRT*) algorithm is proposed. Firstly, a probabilistically adaptive target bias strategy is introduced based on the bidirectional Informed-RRT* to reduce the randomness of the original bidirectional RRT* search and improve sampling efficiency. Secondly, the Artificial Potential Field (APF) method is integrated into the path expansion process of the bidirectional search trees to reduce the number of algorithm iterations. Simultaneously, during the path growth phase, an adaptive step size growth strategy is adopted, which dynamically adjusts the step size according to the expansion trend of the search tree to avoid local optima and shorten the path search time until an initial path is generated. Finally, redundant nodes in the generated path are removed using the triangle inequality principle, and the path is smoothed using cubic B-spline curves to obtain the optimal planned path. Simulation comparisons of the improved algorithm were conducted in two-dimensional environments under three different scenarios. The results show that the improved algorithm effectively enhances relevant performance. Applying the improved algorithm to a physical platform further demonstrates its effectiveness and feasibility.

KEYWORDS

Robotic Arm; Path planning algorithm; Bidirectional target bias; Adaptive step size; Artificial Potential Field (APF); B-spline smoothing

CITE THIS PAPER

Zhai Linlin, Fu Jiajie, Research on Robotic Arm Path Planning Algorithm Based on Bidirectional Target-Biased APF-Informed-RRT* Algorithm. Journal of Artificial Intelligence Practice (2025) Vol. 8: 126-133. DOI: http://dx.doi.org/10.23977/jaip.2025.080316.

REFERENCES

[1] Wu Kai, Yang Jianzhong, Huang Si, et al. Efficient Path Planning for Robotic Arm Using Improved RRT Algorithm [J]. Mechanical Science and Technology, 2024.
[2] Liu Yang, Sun Rui, Luo Jie, et al. Path Planning for Measurement Robotic Arm Based on Improved RRT Algorithm [J]. Machine Design and Research, 2024, 40(5).
[3] Karaman S, Frazzoli E. Sampling-based algorithms for optimal motion planning[J]. The International Journal of Robotics Research, 2011, 30(7): 846-894.
[4] Kuffner J J, LaValle S M. RRT-connect: An efficient approach to single-query path planning[C]//Proceedings of the 2000 IEEE International Conference on Robotics and Automation. San Francisco, USA: IEEE, 2000: 995-1001.
[5] Gammell J D, Srinivasa S S, Barfoot T D. Informed RRT*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic[C]//2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. Chicago, USA: IEEE, 2014: 2997-3004.
[6] Liu Xiaosong, Kang Lei, Shan Zebiao, et al. Robotic Arm Path Planning Based on Bidirectional Target-Biased APF-Informed-RRT* Algorithm [J]. Journal of Electronic Measurement and Instrumentation, 2024, 38(6): 75-83. DOI: 10.13382/j.jemi.B2407196.

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